Regulation of global gene expression in the bone marrow microenvironment by androgen: Androgen ablation increases insulin‐like growth factor binding protein‐5 expression
Bibliographic record
Abstract
BACKGROUND: Prostate cancer frequently metastasizes to bone. Androgen suppression treatment is initially highly effective, but eventually results in resistant cancer cells. This study evaluates the effects of androgen suppression on the bone and bone marrow (BM). In particular we questioned whether the androgen therapy could adversely facilitate prostate cancer progression through an increase growth factor secretion by the bone microenvironment. METHODS: Global gene expression is analyzed on mPEDB DNA microarrays. Insulin-like growth factor binding protein-5 (IGFBP5) is detected by immunohistochemistry in mouse tissues and its regulation measured by qPCR and Western blotting in human BM stromal cells. Effects of extracellular matrix-associated IGFBP5 on human prostate epithelial cells are tested in an MTS cell-growth assay. RESULTS: Castration increases expression of 159 genes (including 4 secreted cytokines) and suppresses expression of 84 genes. IGFBP5 is most consistently increased and the increase in expression is reversed by testosterone administration. IGFBP5 protein is detected in vivo in osteoblasts, BM stromal cells, and endothelial cells. Primary human stromal cell cultures secrete IGFBP5. In vitro, treatment of immortalized human marrow stromal cells with charcoal-stripped serum increases IGFBP5 mRNA expression, which is reversed by androgen supplementation. IGFBP5 is incorporated into the extracellular matrix. Further, IGFBP5 immobilized on extracellular matrices of stromal cells enhances the growth of immortalized prostate epithelial cells. CONCLUSIONS: Androgen suppressive therapy increases IGFBP5 in the BM microenvironment and thereby may facilitate the progression of prostate cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".